State Observers and Unknown Input Estimators for Discrete-Time Nonlinear Systems Characterized by Incremental Multiplier Matrices

2020 59th IEEE Conference on Decision and Control (CDC) ◽

10.1109/cdc42340.2020.9304433 ◽

2020 ◽

Author(s):

Badriah Alenezi ◽

Mukai Zhang ◽

Stefen Hui ◽

Stanislaw H. Zak

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Unknown Input ◽

State Observers

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On convergence of extended state observers for discrete-time nonlinear systems

2015 34th Chinese Control Conference (CCC) ◽

10.1109/chicc.2015.7259694 ◽

2015 ◽

Author(s):

Yuan Huang ◽

Junzheng Wang ◽

Dawei Shi

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Extended State ◽

State Observers

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Adaptive control for discrete-time nonlinear systems with non-sector nonlinearities and unknown input gain

2017 Chinese Automation Congress (CAC) ◽

10.1109/cac.2017.8243533 ◽

2017 ◽

Author(s):

Miao Yu ◽

Deqing Huang

Keyword(s):

Adaptive Control ◽

Nonlinear Systems ◽

Discrete Time ◽

Unknown Input ◽

Sector Nonlinearities

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Discrete-Time Sliding-Mode State and Unknown Input Estimations for Nonlinear Systems

IEEE Transactions on Industrial Electronics ◽

10.1109/tie.2008.2007035 ◽

2009 ◽

Vol 56 (9) ◽

pp. 3443-3452 ◽

Author(s):

K.C. Veluvolu ◽

Yeng Chai Soh

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Sliding Mode ◽

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State and unknown input observers for discrete-time nonlinear systems

2016 IEEE 55th Conference on Decision and Control (CDC) ◽

10.1109/cdc.2016.7799365 ◽

2016 ◽

Author(s):

Ankush Chakrabarty ◽

Stanislaw H. Zak ◽

Shreyas Sundaram

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Unknown Input ◽

Unknown Input Observers

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A Nearer Optimal and Faster Trained Value Iteration ADP for Discrete-Time Nonlinear Systems

IEEE Access ◽

10.1109/access.2021.3051984 ◽

2021 ◽

Vol 9 ◽

pp. 14933-14944

Author(s):

Junping Hu ◽

Gen Yang ◽

Zhicheng Hou ◽

Gong Zhang ◽

Wenlin Yang ◽

...

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Value Iteration

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Iterative learning scheme design for a class of discrete-time nonlinear systems

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9189050 ◽

2020 ◽

Author(s):

Yamiao Zhang ◽

Jian Liu ◽

Yuan Yuan

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Iterative Learning ◽

Scheme Design ◽

Learning Scheme

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Event-Triggered Optimal Parallel Tracking Control for Discrete-Time Nonlinear Systems

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2021.3073429 ◽

2021 ◽

pp. 1-13

Author(s):

Jingwei Lu ◽

Qinglai Wei ◽

Yujia Liu ◽

Tianmin Zhou ◽

Fei-Yue Wang

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Tracking Control ◽

Event Triggered

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Stability Analysis for a class of Stochastic Nonlinear Systems Based on The Approximate Discrete-Time Models

2020 39th Chinese Control Conference (CCC) ◽

10.23919/ccc50068.2020.9189173 ◽

2020 ◽

Author(s):

Niankun Zhang ◽

Yu Kang ◽

Peilong Yu

Keyword(s):

Stability Analysis ◽

Nonlinear Systems ◽

Discrete Time ◽

Stochastic Nonlinear Systems ◽

Discrete Time Models

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Fault estimation and fault tolerant control for discrete-time nonlinear systems with perturbation by a mixed design scheme

Journal of the Franklin Institute ◽

10.1016/j.jfranklin.2020.12.024 ◽

2020 ◽

Author(s):

Ximing Yang ◽

Tieshan Li ◽

Yue Wu ◽

Yang Wang ◽

Yue Long

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Fault Estimation ◽

Mixed Design ◽

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A data-driven immersion technique for linearization of discrete-time nonlinear systems

IFAC-PapersOnLine ◽

10.1016/j.ifacol.2020.12.845 ◽

2020 ◽

Vol 53 (2) ◽

pp. 869-874

Author(s):

Zheming Wang ◽

Raphaël M. Jungers

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Data Driven ◽

Immersion Technique

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